As performance requirements and throughput demands increase, semiconductor fabrication process control has become increasingly crucial. However, as process geometries decrease, such as from 65 to 45 nanometer and beyond, it may be challenging to keep process variations at acceptable levels. As such, the processes may suffer from losses in tool productivity, increased operator interaction, yield loss, and higher rework rates, all possibly leading to higher costs. Advanced Process Control (APC), which may consist of models and feedback systems among other process control techniques, has been widely used to help alleviate some of the variations.
APC techniques generally have multiple processing stages. A problem with existing APC techniques is that they typically assume that the performance targets associated with each processing stage will be achieved at the end of each processing stage. In other words, the existing APC techniques typically do not take into account drifts that occur during processing. In reality, each processing stage may contain a certain amount of processing drift. Over time, the processing drifts will accumulate and may cause substantially deviations to a final performance target of the APC process.
Consequently, although existing APC techniques have been generally adequate for their intended purposes, they have not been entirely satisfactory in all respects.